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Big Data During Crisis: Lessons from Hurricane Irene

This project aims to evaluate the potential of leveraging big social data during a disaster or emergency to characterize transportation issues and monitor the dynamic needs of the affected population. The research is based on an in-depth case study of Hurricane Irene, where flooding severed transportation links to isolate communities from critical supplies. The project plans to engage agencies and organizations at the federal, state, municipal and grassroots levels to understand the needs of decision makers and define analytical requirements to leverage big data. The projects anticipates two primary contributions based on the in-depth case study of Hurricane Irene: (1) to characterize the potential of big data from social networks to complement sensor networks in creating actionable information in a crisis and (2) to further develop methodologies such as Natural Language Processing (NLP) to analyze these sources of big data.